Librarian, researcher and information specialist. The concept for AI Augmented Reading emerged from professional expertise — years of engagement with how people read and where they struggle.
The question that became Augmented Reading is one that anyone who works professionally with how people read will recognise immediately. Why, in an era of sophisticated artificial intelligence, does the experience of reading a digital text remain essentially unchanged from 2007?
Dictionary lookup, highlighting, annotation, text-to-speech — every feature available on a contemporary e-reader or reading platform operates at the word level. None of them addresses the reader who encounters a passage describing something inherently visual: a storm system moving across the North Atlantic, a battle formation on the ridge at Waterloo, the architecture of a medieval scriptorium, the mechanism by which a beta-blocker interrupts a cardiac signalling cascade.
That reader must either leave the document and search externally — losing their place, their momentum, and often the context of what they were reading — or read on without the understanding the passage deserved. This is not a content problem. It is a method problem. The information needed to generate a contextually appropriate visual is already present in the text. What was missing was a system that could read the passage, understand what kind of visual it was describing, and render that visual inline.
The insight emerged from sustained professional engagement with information, reading and comprehension across library services, academic research, digital communication and educational technology. Published research on how digital information decays and becomes inaccessible — link rot, reference rot, the instability of web-based scholarly resources — gave direct professional grounding in the question of what happens when readers cannot access or comprehend the information they need. Augmented Reading addresses the complementary problem: not information that cannot be found, but information that cannot be visualised. It is not a technology solution looking for a problem. It is a professional observation about a persistent gap in the reading experience, with a working method for closing it.
Colm O'Connor is a librarian, researcher and information specialist based in Waterford, Ireland. The concept for AI Augmented Reading is a personal venture, developed independently of any institutional role, with extensive ground in library services, clinical information work, academic publishing and educational technology.